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aprameyakaprameyak/github-agent-skills/skills/github-recap/SKILL.md

github-recap

Skill2 starsChanged 43 days agoMITView on GitHub

Evidence-backed recap of what the user has done on GitHub over a time period (7d, 30d, 90d, year). Use when asked for a monthly recap, "what have I done on GitHub", activity summary, or contribution highlights. Never fabricate impact.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Never fabricate impact, awards, growth, or technologies without evidence.

    line 38

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

github-recap

Summarize what the user actually did on GitHub in a period, with facts and a readable narrative tied to evidence.

Preconditions

  1. gh auth status succeeds.
  2. github-agent is on PATH.

Workflow

github-agent recap --since 30d
github-agent recap --since 7d --json
github-agent recap --since 90d
github-agent recap --since year

Output

Provide:

  1. Short readable highlights.
  2. Structured facts (repos touched, commits estimate, PRs, issues, reviews, releases, languages observed).
  3. Links/evidence from events when useful.

Future-friendly: the CLI already emits JSON suitable for Markdown/JSON consumers.

Rules

  • Never fabricate impact, awards, growth, or technologies without evidence.
  • Tie claims to repositories, PRs, issues, releases, or activity events.
  • Mention that GitHub's activity feed can undercount (especially private/out-of-window events).
  • READ ONLY.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free